Recognizing the importance of competition analysis in telecommunications markets is essential to improve conditions for users and companies. Several indices in the literature assess competition in these markets, mainly through company concentration. Artificial Intelligence (AI) emerges as an effective solution to process large volumes of data and manually detect patterns that are difficult to identify. This article presents an AI model based on the LINDA indicator to predict whether oligopolies exist. The objective is to offer a valuable tool for analysts and professionals in the sector. The model uses the traffic produced, the reported revenues, and the number of users as input variables. As output parameters of the model, the LINDA index is obtained according to the information reported by the operators, the prediction using Long-Short Term Memory (LSTM) for the input variables, and finally, the prediction of the LINDA index according to the prediction obtained by the LSTM model. The obtained Mean Absolute Percentage Error (MAPE) levels indicate that the proposed strategy can be an effective tool for forecasting the dynamic fluctuations of the communications market.

The power of Artificial Intelligence (AI) combined with the surgeons’ expertise leads to breakthroughs in surgical care, bringing new hope to patients. Utilizing deep learning-based computer vision techniques in surgical procedures will enhance the healthcare industry. Laparoscopic surgery holds excellent potential for computer vision due to the abundance of real-time laparoscopic recordings captured by digital cameras containing significant unexplored information. Furthermore, with computing power resources becoming increasingly accessible and Machine Learning methods expanding across various industries, the potential for AI in healthcare is vast. There are several objectives of AI’s contribution to laparoscopic surgery; one is an image guidance system to identify anatomical structures in real-time. However, few studies are concerned with intraoperative anatomy recognition in laparoscopic surgery. This study provides a comprehensive review of the current state-of-the-art semantic segmentation techniques, which can guide surgeons during laparoscopic procedures by identifying specific anatomical structures for dissection or avoiding hazardous areas. This review aims to enhance research in AI for surgery to guide innovations towards more successful experiments that can be applied in real-world clinical settings. This AI contribution could revolutionize the field of laparoscopic surgery and improve patient outcomes.

Arabic rhetoric has traditionally relied on ancient texts and human interpretation for teaching purposes. The study investigates ChatGPT’s ability to analyze and interpret Arabic rhetorical devices, specifically examining its capacity to handle cultural and contextual elements in rhetorical analysis. Drawing on institutional implementation frameworks and recent educational technology research, this study examines policy considerations for Arabic rhetoric education in an AI-driven environment, with a particular focus on sustainable digital infrastructure development and systematic reforms needed to support AI integration. The study employed the comparative approach to analyze eight rhetorical examples, including metaphors (“Zaid is a lion”), similes (“Someone is a sea”), and metonymy (“A person full of ash”), then compare ChatGPT’s interpretations with traditional explanations from classical Arabic rhetoric texts, particularly “Dala’il al-I’jaaz” by al-Jurjani. The results demonstrate that ChatGPT can provide basic interpretations of simple rhetorical devices, but it struggles with understanding cultural contexts and multiple layers of meaning inherent in Arabic rhetoric. The findings indicate that AI tools, despite their potential for modernizing rhetoric education, currently serve best as supplementary teaching aids rather than replacements for traditional interpretative methods in Arabic rhetoric instruction.

The study aims to explore the role of artificial intelligence in enhancing the efficiency of public relations practitioners in Jordanian telecommunication companies. This study belongs to the category of descriptive research and adopted a survey methodology. The study surveyed (86) individuals representing the community of public relations practitioners and customer service personnel in the Jordanian telecommunication companies Zain and Orange.The study findings revealed that less experienced public relations personnel in Zain and Orange, with less than five years of experience, exhibit greater acceptance and enthusiasm for using artificial intelligence applications compared to their more experienced counterparts. The study also indicated that most public relations practitioners in Zain and Orange perceive artificial intelligence applications to have a moderate to significant contribution to achieving public relations functions and enhancing their work, reflecting technological advancement and the need to adapt to rapid changes in the business environment. Moreover, the study also discussed the limits, including that artificial intelligence can analyze large amounts of data related to the market and the audience, which provides further research and study.

In the Fourth Industrial Revolution (4IR) era, the rapid digitalisation of services poses both opportunities and challenges for the banking sector. This study addresses how adopting artificial intelligence (AI) and online and mobile banking advancements can influence customer satisfaction, particularly in Kaduna State, Nigeria. Despite significant investments in AI and digital banking technologies, banks often struggle to align these innovations with customer expectations and satisfaction. Using Structural Equation Modeling (SEM), this research investigates the impact of customer satisfaction with online banking (C_O) on AI integration (I_A) and mobile banking convenience (C_M). The SEM model reveals that customer satisfaction with online banking significantly influences AI integration (path coefficient of 0.40) and mobile banking convenience (path coefficient of 0.68). These results highlight a crucial problem: while technological advancements in banking are growing, their effectiveness is highly dependent on customer satisfaction with existing digital services. The study underscores the need for banks to prioritise enhancing online banking experiences as a strategic lever to improve AI integration and mobile banking convenience. Consequently, the research recommends that Nigerian banks develop comprehensive frameworks to evaluate and optimise their technology integration strategies, ensuring that technological innovations align with customer needs and expectations in the rapidly evolving digital landscape.